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About the projects: We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.
About the Role:
We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public GitHub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and quality
Why Join Us
Turing is one of the world's fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You'll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.
What does day-to-day look like:
Required Skills:
Nice to Have:
Offer Details:
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Job ID: 149018013
Skills:
Solid Principles, Apache Spark, Sql, Clustering, Python, data pipelines, data workflows, clean code practices, architecture patterns, data models, partitioning, real-time fraud detection, streaming replication
Skills:
Design Patterns, System Design, Apache Spark, Python, Sql, software engineering principles, distributed data systems, architecture, clean code, Big Data processing
Skills:
Git, Javascript, Data Structures, Python, Sql, HTML/CSS
Skills:
Algorithms, Apis, Database Technologies, data structures, Python, Web Services, unit tests, CI CD pipelines
Skills:
Machine Learning, Exploratory Data Analysis, Technical Documentation, Deep Learning, Rest Apis, Python, Data Ingestion, Performance Optimization, End-to-end ML pipelines, Feature Engineering, Data Preprocessing, Ai, Model Training, Code Quality
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